scholarly journals Compartmentalization and Cell Division through Molecular Discreteness and Crowding in a Catalytic Reaction Network

Life ◽  
2014 ◽  
Vol 4 (4) ◽  
pp. 586-597 ◽  
Author(s):  
Atsushi Kamimura ◽  
Kunihiko Kaneko
Keyword(s):  
Cell Division ◽  
Catalytic Reaction ◽  
Reaction Network

scholarly journals Revisiting Catalytic Cycles: A Broader View Through the Energy Span Model

2020 ◽  
Author(s):  
Diego Garay-Ruiz ◽  
Carles Bo
Keyword(s):  
Catalytic Reaction ◽  
Reaction Mechanisms ◽  
Computational Study ◽  
Reaction Network ◽  
Co2 Hydrogenation ◽  
Level Of Detail ◽  
Reaction Pathways ◽  
Catalytic Systems ◽  
Computational Code ◽  
Catalytic Cycles

<div><div><div><p>The computational study of catalytic processes allows discovering really intricate and detailed reaction mechanisms that involve many species and transformations. This increasing level of detail can even result detrimental when drawing conclusions from the computed mechanism, as many co-existing reaction pathways can be in close com- petence. Here we present a reaction network-based implementation of the energy span model in the form of a computational code, gTOFfee, capable of dealing with any user-specified reaction network. This approach, compared to microkinetic simulations, enables a much easier and straightforward analysis of the performance of any catalytic reaction network. In this communication, we will go through the foundations and appli- cability of the underlying model, and will tackle the application to two relevant catalytic systems: homogeneous Co-mediated propene hydroformylation and heterogeneous CO2 hydrogenation over Cu(111).</p></div></div></div>

scholarly journals Molecular Diversity and Network Complexity in Growing Protocells

2019 ◽  
Author(s):  
Atsushi Kamimura ◽  
Kunihiko Kaneko
Keyword(s):  
Catalytic Reaction ◽  
Host Species ◽  
Molecular Diversity ◽  
Reaction Network ◽  
Cellular Growth ◽  
Cell Reproduction ◽  
A Cell ◽  
Molecular Components ◽  
Growth Scaling ◽  
Cellular Components

AbstractA great variety of molecular components is encapsulated in cells. Each of these components is replicated for cell reproduction. To address an essential role of the huge diversity of cellular components, we study a model of protocells that convert resources into catalysts with the aid of a catalytic reaction network. As the resources are limited, it is shown that diversity in intracellular components is increased to allow the use of diverse resources for cellular growth. Scaling relation is demonstrated between resource abundances and molecular diversity. We then study how the molecule species diversify and complex catalytic reaction networks develop through the evolutionary course. It is shown that molecule species first appear, at some generations, as parasitic ones that do not contribute to replication of other molecules. Later, the species turn to be host species that support the replication of other species. With this successive increase of host species, a complex joint network evolves. The present study sheds new light on the origin of molecular diversity and complex reaction network at the primitive stage of a cell.

scholarly journals Molecular Diversity and Network Complexity in Growing Protocells

Life ◽  
2019 ◽  
Vol 9 (2) ◽  
pp. 53
Author(s):  
Atsushi Kamimura ◽  
Kunihiko Kaneko
Keyword(s):  
Molecular Species ◽  
Catalytic Reaction ◽  
Molecular Diversity ◽  
Reaction Network ◽  
Cellular Growth ◽  
Reaction Networks ◽  
Cell Reproduction ◽  
A Cell ◽  
Molecular Components ◽  
Cellular Components

A great variety of molecular components is encapsulated in cells. Each of these components is replicated for cell reproduction. To address the essential role of the huge diversity of cellular components, we studied a model of protocells that convert resources into catalysts with the aid of a catalytic reaction network. As the resources were limited, the diversity in the intracellular components was found to be increased to allow the use of diverse resources for cellular growth. A scaling relation was demonstrated between resource abundances and molecular diversity. In the present study, we examined how the molecular species diversify and how complex catalytic reaction networks develop through an evolutionary course. At some generations, molecular species first appear as parasites that do not contribute to the replication of other molecules. Later, the species turn into host species that contribute to the replication of other species, with further diversification of molecular species. Thus, a complex joint network evolves with this successive increase in species. The present study sheds new light on the origin of molecular diversity and complex reaction networks at the primitive stage of a cell.

The catalytic kinetics and cfd simulation of multi-stage combined removal of acrylonitrile tail gas

2021 ◽  
pp. 115-125
Author(s):  
Zhao Du ◽  
◽  
Qian Liu ◽  
Yuxuan Yang ◽  
◽  
...  
Keyword(s):  
Mathematical Model ◽  
Kinetic Model ◽  
Catalytic Reaction ◽  
Cfd Simulation ◽  
Reaction Network ◽  
External Diffusion ◽  
Quantitative Calculation ◽  
Dynamic Factors ◽  
Multi Stage ◽  
Catalytic Kinetics

There is no kinetic data and rate equation that can be used directly for catalytic combustion of acrylonitrile tail gas, which leads to the multi-stage combined catalytic kinetic model of acrylonitrile tail gas collaborative removal. In the actual application process, affected by the internal and external diffusion, this paper proposes the multi-stage combined catalytic kinetic research and CFD simulation analysis of acrylonitrile tail gas collaborative removal. Based on the judgment of multi-stage combined catalytic reaction rules of acrylonitrile tail gas collaborative removal, the multi-stage combined catalytic reaction network of acrylonitrile tail gas collaborative removal is solved by matrix transformation. The possible reaction path in the multi-stage combined catalytic reaction network of acrylonitrile tail gas collaborative removal is solved. For quantitative calculation of product distribution, each step of reaction parameters and dynamic factors are required. According to the mechanism of positive carbon ion reaction, materials were used Studio software and genetic algorithm are used to calculate the dynamic factors and determine the dynamic parameters; the grid automatic generator AutoGrid5 embedded in the Fine/TurboTM software package is used to generate the CFD simulation network, and the iterative algorithm is used to calculate the limit value of the CFD simulation; the S-A model in the CFD simulation platform is used to get the modified value of the dynamic mathematical model, and the dynamic factors and parameters are brought into it to establish the CA mathematical model of multi-stage combined catalytic kinetics for the CO removal of olefine and nitrile tail gas. The experimental results show that, under the same experimental device and parameters, the internal and external diffusion effects of the multi-stage combined catalytic kinetic model of acrylonitrile tail gas collaborative removal are detected. The multi-stage combined catalytic kinetic model of acrylonitrile tail gas collaborative removal in this study uses 10-20 mesh catalyst, and the retention time of acrylonitrile tail gas is less than 4.62 s, the internal and external diffusion will not affect the acrylonitrile tail gas collaborative removal The practical application of the kinetic model for the removal of multi-stage combined catalysis.

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